Professor Tapabrata Ray

Professor
School of Engineering and Information Technology
+61 2 5114 5201
+61 2 6268 8276

LOCATION

Building 17 Room 202
School of Engineering and Information Technology, The University of New South Wales, Australian Defence Force Academy, PO Box 7916, Canberra BC ACT 2610, AUSTRALIA

  • ABOUT
  • PUBLICATIONS

Tapabrata Ray is a Professor with the School of Engineering and Information Technology. He is the founder and leader of the Multidisciplinary Design Optimization Research Group at UNSW, Canberra. Further details of his research is listed in the link below www.mdolab.net

Books

Prusty BG; Sul J; Ray T, 2011, Fatigue behaviour of short fibre composites, Nova Science Publishers Inc, NY, USA, https://www.novapublishers.com/catalog/product_info.php?products_id=18040

Book Chapters

Bhattacharjee KS; Singh HK; Ray T, 2020, 'Many-objective optimization with limited computing budget', in Studies in Computational Intelligence, pp. 17 - 46, http://dx.doi.org/10.1007/978-3-030-18764-4_2

Hassanein O; Anavatti S; Ray T, 2018, 'Autonomous Underwater Vehicles', in Meng Joo E (ed.), Intelligent Marine and Aerial Vehicles: Theory and Applications, Nova Publishers, https://novapublishers.com/shop/intelligent-marine-and-aerial-vehicles-theory-and-applications/

Bhattacharjee KS; Isaacs A; Ray T, 2016, 'Multi-objective optimization using an evolutionary algorithm embedded with multiple spatially distributed surrogates', in Multi-Objective Optimization: Techniques and Applications in Chemical Engineering (Second Edition), pp. 135 - 156, http://dx.doi.org/10.1142/9789812836526_0005

Anavatti SG; ray T, 2016, 'A Game-Theoretic Approach to the Analysis of Traffic Assignment', in singh H (ed.), Intelligent and Evolutionary Systems The 20th Asia Pacific Symposium, IES 2016, Canberra, Australia, November 2016, Proceedings, Springer, pp. 17 - 30, http://dx.doi.org/10.1007/978-3-319-49049-6_2

Anavatti SG; li C; ray T, 2016, 'A game-theoretic approach to the analysis of Traffic Assignment', in Intelligent and Evolutionary Systems The 20th Asia Pacific Symposium, IES 2016, Canberra, Australia, November 2016, Proceedings, Springer, pp. 17 - 30, http://dx.doi.org/10.1007/978-3-319-49049-6_2

Tajbakhsh SE; Ray T; Reed MC, 2015, 'An Evolutionary Approach to Resource Allocation in Wireless Small Cell Networks', in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer International Publishing, pp. 718 - 724, http://dx.doi.org/10.1007/978-3-319-24540-9_59

Bhattacharjee KS; Ray T, 2015, 'Cost to Evaluate Versus Cost to Learn? Performance of Selective Evaluation Strategies in Multiobjective Optimization', in AI 2015: Advances in Artificial Intelligence, Springer, pp. 63 - 75, http://dx.doi.org/10.1007/978-3-319-26350-2_6

Bhattacharjee KS; Ray T, 2015, 'An Evolutionary Algorithm with Classifier Guided Constraint Evaluation Strategy for Computationally Expensive Optimization Problems', in AI 2015: Advances in Artificial Intelligence, Springer, pp. 49 - 62, http://dx.doi.org/10.1007/978-3-319-26350-2_5

Hassanein O; Anavatti SG; Ray T, 2013, 'On-line adaptive fuzzy modeling and control for autonomous underwater vehicle', in Recent Advances in Robotics and Automation, Springer, Heidelberg, pp. 57 - 70, http://dx.doi.org/10.1007/978-3-642-37387-9_4

Ray T; Sarker R, 2012, 'Memetic algorithms in constrained optimization', in Neri F; Cotta C; Moscato P (ed.), Handbook of Memetic Algorithms, Springer, Germany, pp. 135 - 151, http://dx.doi.org/10.1007/978-3-642-23247-3_9

Sarker RA; Ray T, 2010, 'Agent Based Evolutionary Approach: An Introduction', in Sarker RA; Ray T (ed.), AGENT-BASED EVOLUTIONARY SEARCH, edn. Adaptation Learning and Optimization, SPRINGER-VERLAG BERLIN, pp. 1 - 11, http://dx.doi.org/10.1007/978-3-642-13425-8_1

Singh HK; Ray T, 2010, 'Divide and Conquer in Coevolution: A Difficult Balancing Act', in Sarker R; Ray T (ed.), Agent-Based Evolutionary Search (Book series: Adaption, learning and optimization, vol. 5), edn. Adaptation Learning and Optimization, Springer-Verlag, Berlin / Heidelberg, pp. 121 - 142, http://dx.doi.org/10.1007/978-3-642-13425-8_6

Sarker R; Ray T, 2010, 'Agent based Evolutionary Approach: An Introduction', in Sarker R; Ray T (ed.), Agent-Based Evolutionary Search (Book series: Adaption, learning and optimization, vol. 5), edn. 1, Springer-Verlag, Berlin / Heidelberg, pp. 1 - 11, http://dx.doi.org/10.1007/978-3-642-13425-8

Ray T; Isaacs A; Smith WF, 2009, 'A Memetic Algorithm for Dynamic Multiobjective Optimization', in Goh CK; Ong YS; Tan KC (ed.), Studies in computational intelligence / Multi-Objective Memetic Algorithms, Springer, Berlin / Heidelberg, pp. 353 - 367, http://dx.doi.org/10.1007/978-3-540-88051-6_16

Ray T; Singh HK; Isaacs A; Smith WF, 2009, 'Infeasibility Driven Evolutionary Algorithm for Constrained Optimization', in Montes EEM (ed.), Constraint-Handling in Evolutionary Optimization, Springer Publishing Company, Berlin, Germany, pp. 145 - 165, http://dx.doi.org/10.1007/978-3-642-00619-7_7

Ray T; Isaacs A; Smith WF, 2009, 'Surrogate Assisted Evolutionary Algorithm for Multi-objective Optimization', in Rangaih GP (ed.), Multi-objective Optimization: Techniques and Applications in Chemical Engineering, edn. Har/Cdr edition (December 22, 2008), World Scientific Publishing, Singapore, pp. 131 - 151, http://www.worldscibooks.com/etextbook/7088/7088_toc.pdf

Isaacs A; Ray T; Smith WF, 2008, 'Set Representation and Multi-parent Learning within an Evolutionary Algorithm for Optimal Design of Trusses', in Chen YP; Lim LH (ed.), Linkage In Evolutionary Computation, Springer Publishing Company, pp. 419 - 439, http://dx.doi.org/10.1007/978-3-540-85068-7_17

Ray T; Sarker R, 2007, 'Optimum oil production planning using an evolutionary approach', in Studies in Computational Intelligence - Evolutionary Scheduling, Springer Verlag, pp. 273 - 292, http://dx.doi.org/10.1007/978-3-540-48584-1_10

Ray T, 2006, 'A Neural-Network-Assisted Optimization Framework and Its Use for Optimum-Parameter Identification', in Kamruzzaman J; Begg R; Sarker R (ed.), Artificial Neural Networks in Finance and Manufacturing, Idea Group Publishing, England, pp. 221 - 235, http://dx.doi.org/10.4018/978-1-59140-670-9.ch013

Ray T; Venkata N, 2005, 'Application of Multiobjective optimization in Electromagnetic Design', in Nedjah N; Mourelle LDM (ed.), Application of Multiobjective optimization in Electromagnetic Design, edn. first, Nova Science Publications, New York, USA, pp. 77 - 100, http://books.google.com.au/books?id=UeoV9NNJ_8oC&pg=PA77&lpg=PA77&dq=Application+of+Multiobjective+optimization+in+Electromagnetic+Design&source=bl&ots=3QRvNgt6u4&sig=DAY9jeGp9rk5iAZT0Xp9yhO4lXs&hl=en

Journal articles

Tarek M; Ray T, 2020, 'Adaptive continuation solid isotropic material with penalization for volume constrained compliance minimization', Computer Methods in Applied Mechanics and Engineering, vol. 363, http://dx.doi.org/10.1016/j.cma.2020.112880

Rana MJ; Zaman F; Ray T; Sarker R, 2020, 'Heuristic enhanced evolutionary algorithm for community microgrid scheduling', IEEE Access, vol. 8, pp. 76500 - 76515, http://dx.doi.org/10.1109/ACCESS.2020.2989795

Habib A; Singh HK; Chugh T; Ray T; Miettinen K, 2019, 'A multiple surrogate assisted decomposition-based evolutionary algorithm for expensive multi/many-objective optimization', IEEE Transactions on Evolutionary Computation, vol. 23, pp. 1000 - 1014, http://dx.doi.org/10.1109/TEVC.2019.2899030

Chand S; Singh H; Ray T, 2019, 'Evolving rollout-justification based heuristics for resource constrained project scheduling problems', Swarm and Evolutionary Computation, vol. 50, http://dx.doi.org/10.1016/j.swevo.2019.07.002

Habib A; K. Singh H; Ray T, 2019, 'A multiple surrogate assisted multi/many-objective multi-fidelity evolutionary algorithm', Information Sciences, vol. 502, pp. 537 - 557, http://dx.doi.org/10.1016/j.ins.2019.06.016

Singh HK; Islam MM; Ray T; Ryan M, 2019, 'Nested evolutionary algorithms for computationally expensive bilevel optimization problems: Variants and their systematic analysis', Swarm and Evolutionary Computation, vol. 48, pp. 329 - 344, http://dx.doi.org/10.1016/j.swevo.2019.05.002

Liu C; Zhao Q; Yan B; Elsayed S; Ray T; Sarker R, 2019, 'Adaptive Sorting-Based Evolutionary Algorithm for Many-Objective Optimization', IEEE Transactions on Evolutionary Computation, vol. 23, pp. 247 - 257, http://dx.doi.org/10.1109/TEVC.2018.2848254

Liu Z; Bhattacharjee KS; Tian FB; Young J; Ray T; Lai JCS, 2019, 'Kinematic optimization of a flapping foil power generator using a multi-fidelity evolutionary algorithm', Renewable Energy, vol. 132, pp. 543 - 557, http://dx.doi.org/10.1016/j.renene.2018.08.015

Chand S; Singh H; Ray T, 2019, 'Evolving heuristics for the resource constrained project scheduling problem with dynamic resource disruptions', Swarm and Evolutionary Computation, vol. 44, pp. 897 - 912, http://dx.doi.org/10.1016/j.swevo.2018.09.007

Singh HK; Ray T; Bhattacharjee KS, 2018, 'Distance based subset selection for benchmarking in evolutionary multi/many-objective optimization', IEEE Transactions on Evolutionary Computation, pp. 1 - 10, http://dx.doi.org/10.1109/TEVC.2018.2883094

Huynh QN; Chand S; Singh HK; Ray T, 2018, 'Genetic Programming With Mixed-Integer Linear Programming-Based Library Search', IEEE Transactions on Evolutionary Computation, vol. 22, pp. 733 - 747, http://dx.doi.org/10.1109/TEVC.2018.2840056

Elsayed S; Sarker R; Coello CC; Ray T, 2018, 'Adaptation of operators and continuous control parameters in differential evolution for constrained optimization', Soft Computing, vol. 22, pp. 6595 - 6616, http://dx.doi.org/10.1007/s00500-017-2712-6

Habib A; Singh HK; Ray T, 2018, 'A multiple surrogate assisted evolutionary algorithm for optimization involving iterative solvers', Engineering Optimization, vol. 50, pp. 1625 - 1644, http://dx.doi.org/10.1080/0305215X.2017.1401068

Zaman F; Elsayed SM; Ray T; Sarkerr RA, 2018, 'Evolutionary Algorithms for Finding Nash Equilibria in Electricity Markets', IEEE Transactions on Evolutionary Computation, vol. 22, pp. 536 - 549, http://dx.doi.org/10.1109/TEVC.2017.2742502

Bhattacharjee KS; Singh HK; Ray T, 2018, 'Multiple surrogate-Assisted many-objective optimization for computationally expensive engineering design', Journal of Mechanical Design, Transactions of the ASME, vol. 140, http://dx.doi.org/10.1115/1.4039450

Chand S; Huynh Q; Singh H; Ray T; Wagner M, 2018, 'On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems', Information Sciences, vol. 432, pp. 146 - 163, http://dx.doi.org/10.1016/j.ins.2017.12.013

Islam MM; Singh HK; Ray T; Sinha A, 2017, 'An enhanced memetic algorithm for Single-Objective bilevel optimization problems', Evolutionary Computation, vol. 25, pp. 607 - 642, http://dx.doi.org/10.1162/EVCO_a_00198

Elsayed S; Sarker R; Ray T; Coello CC, 2017, 'Consolidated optimization algorithm for resource-constrained project scheduling problems', Information Sciences, vol. 418-419, pp. 346 - 362, http://dx.doi.org/10.1016/j.ins.2017.08.023

Alam K; Ray T; Anavatti SG, 2017, 'Design Optimization of an Unmanned Underwater Vehicle Using Low- A nd High-Fidelity Models', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, pp. 2794 - 2808, http://dx.doi.org/10.1109/TSMC.2015.2390592

Islam MM; Singh HK; Ray T, 2017, 'A surrogate assisted approach for single-objective bilevel optimization', IEEE Transactions on Evolutionary Computation, vol. 21, pp. 681 - 696, http://dx.doi.org/10.1109/TEVC.2017.2670659

Bhattacharjee KS; Singh HK; Ryan M; Ray T, 2017, 'Bridging the gap: Many-objective optimization and informed decision-making', IEEE Transactions on Evolutionary Computation, vol. 21, pp. 813 - 820, http://dx.doi.org/10.1109/TEVC.2017.2687320

Zhang Z; Zhan C; Shankar K; Morozov EV; Singh HK; Ray T, 2017, 'Sensitivity analysis of inverse algorithms for damage detection in composites', Composite Structures, vol. 176, pp. 844 - 859, http://dx.doi.org/10.1016/j.compstruct.2017.06.019

Li C; Anavatti SG; Ray T, 2017, 'A Path-Based Solution Algorithm for Dynamic Traffic Assignment', Networks and Spatial Economics, vol. 17, pp. 841 - 860, http://dx.doi.org/10.1007/s11067-017-9346-1

Asafuddoula M; Singh HK; Ray T, 2017, 'An Enhanced Decomposition-Based Evolutionary Algorithm With Adaptive Reference Vectors', IEEE Transactions on Cybernetics, vol. 48, pp. 2321 - 2334, http://dx.doi.org/10.1109/TCYB.2017.2737519

Bhattacharjee KS; Singh HK; Ray T, 2017, 'An approach to generate comprehensive piecewise linear interpolation of pareto outcomes to aid decision making', Journal of Global Optimization, vol. 68, pp. 71 - 93, http://dx.doi.org/10.1007/s10898-016-0454-0

Bhattacharjee KS; Singh HK; Ray T, 2017, 'A novel decomposition-based evolutionary algorithm for engineering design optimization', Journal of Mechanical Design, Transactions of the ASME, vol. 139, http://dx.doi.org/10.1115/1.4035862

Branke J; Asafuddoula M; Bhattacharjee KS; Ray T, 2017, 'Efficient Use of Partially Converged Simulations in Evolutionary Optimization', IEEE Transactions on Evolutionary Computation, vol. 21, pp. 52 - 64, http://dx.doi.org/10.1109/TEVC.2016.2569018

Zaman F; Elsayed SM; Ray T; Sarker RA, 2017, 'Co-evolutionary approach for strategic bidding in competitive electricity markets', Applied Soft Computing Journal, vol. 51, pp. 1 - 22, http://dx.doi.org/10.1016/j.asoc.2016.11.049

Hassanein O; Anavatti SG; Shim H; Ray T, 2016, 'Model-based adaptive control system for autonomous underwater vehicles', Ocean Engineering, vol. 127, pp. 58 - 69, http://dx.doi.org/10.1016/j.oceaneng.2016.09.034

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